Search Results - (( java application matching algorithm ) OR ( trust classification model algorithm ))

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  1. 1

    A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

    Published 2014
    “…In order to choose the final output of MLPE, a new voting algorithm named Trust-Sum Voting (TSV) is proposed. …”
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    Thesis
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    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Focused on computational intelligence models, this thesis describes in-depth investigations on two possible directions to design robust and flexible pattern classification models with high performance. …”
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    Thesis
  4. 4

    BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

    Published 2011
    “…Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. …”
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    Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification by Navan, Farhad Pourpanah

    Published 2015
    “…As a result, an agent-based QFAM ensemble model with a new trust measurement and negotiation method is proposed. …”
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    Securing cloud data system (SCDS) for key exposure using AES algorithm by Thabet Albatol, Mohammed Samer Hasan

    Published 2021
    “…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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  11. 11

    Classification and visualization of e-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi by Ahmad Kushairi, Nuwairah Aimi

    Published 2023
    “…Afterward, the system recommends the best shop to purchase from and visualizes the reviews to compare products from different shops. The SVM classifier model successfully classified the reviews with an accuracy of 96.8% during the testing stage of the classification. …”
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